Special Research Initiatives - Grant ID: SR0354753
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communic ....MESH: amalgamating innovative teams of cross-disciplinary collaborators for creativity in Media-arts, E-culture, Science and Humanities. MESH is a cross-disciplinary network that amalgamates a national array of sub-networks of research in digital arts, ICT and cross-cultural and policy negotiation. It boosts Australia's existing cross-disiciplinary strengths in Media-arts, E-culture, Science and Humanities by encouraging existing digital sub-networks to grow together via well-brokered communications and demonstrations online and on-location. Progressively, MESH participants will discover existing harmonies whilst also inventing new languages and protocols leading to breakthroughs in cross-disciplinary collaboration and innovation. MESH encourages a 'paradigm shift' in digital research, realising the extraordinary potential that is ready but latent across Australia's arts and sciences.Read moreRead less
A Scalable Theory of Behavior Composition for Practical Engineering Models of Human Performance. Minimizing human error and maximizing human performance is a major design goal in safety critical systems. The development of methods for affordable human performance modeling has widespread applicability for evaluating user-system interfaces. The compositional method explored here has been shown to make accurate predictions reduce model development time by an order of magnitude. Large safety critica ....A Scalable Theory of Behavior Composition for Practical Engineering Models of Human Performance. Minimizing human error and maximizing human performance is a major design goal in safety critical systems. The development of methods for affordable human performance modeling has widespread applicability for evaluating user-system interfaces. The compositional method explored here has been shown to make accurate predictions reduce model development time by an order of magnitude. Large safety critical applications, such as military or air traffic control systems, would benefit greatly. The proposed work tests whether the compositional methods will scale to more complex domains. The work will be coordinated with Australian industry, academia, and government research efforts.Read moreRead less
Development of a computational model for the prediction of mental workload in air traffic control. The aim of the project is to develop a computational model that can measure the flow of traffic through an air sector, and predict the level of workload that an air traffic controller will experience, as well as the overall risk of breakdowns in separation between aircaft. The purpose is to develop a tool that can be used for the purposes of risk analysis and scenario planning. This is a multidisci ....Development of a computational model for the prediction of mental workload in air traffic control. The aim of the project is to develop a computational model that can measure the flow of traffic through an air sector, and predict the level of workload that an air traffic controller will experience, as well as the overall risk of breakdowns in separation between aircaft. The purpose is to develop a tool that can be used for the purposes of risk analysis and scenario planning. This is a multidisciplinary project, integrating recent models of human memory and reasoning, with formal methods for the analysis of human-computer systems. The project will advance our understanding of human memory and reasoning in complex real-world systems.Read moreRead less